code: def test_fid_function():
      train_samples, test_samples = torch.rand(10, 10), torch.rand(
          10, 10
      )
  
      mu1, sigma1 = train_samples.mean(axis=0), cov(
          train_samples, rowvar=False
      )
      mu2, sigma2 = test_samples.mean(axis=0), cov(
          test_samples, rowvar=False
      )
  
      sigma1 = torch.tensor(sigma1, dtype=torch.float64)
      sigma2 = torch.tensor(sigma2, dtype=torch.float64)
      assert pytest.approx(
          fid_score(mu1, mu2, sigma1, sigma2), rel=1e-5
      ) == pytorch_fid_score.calculate_frechet_distance(
          mu1, sigma1, mu2, sigma2
      )
  
imports: import os
  import re
  from unittest.mock import patch
  import pytest
  import pytorch_fid.fid_score
  import scipy
  import torch
  from numpy import cov
  import ignite.distributed
  from ignite.metrics.gan.fid import FID, fid_score
label_desc: Use image node_id 5 for calling a global function with example usage: test_fid_function() without return types